Agricultural productivity in relation to climate and cropland management in West Africa

Temperature Effect on Rhizome Development in Perennial rice

Traditional agriculture is becoming increasingly not adapted to global climate change. Compared with annual rice, perennial rice has strong environmental adaptation and needs fewer natural resources and labor inputs. Rhizome, a kind of underground stem for rice to achieve perenniallity, can grow underground horizontally and then bend upward, developing into aerial stems. The temperature has a great influence on plant development. To date, the effect of temperature on rhizome development is still unknown. Fine temperature treatment of Oryza longistaminata (OL) proved that compared with higher temperatures (28-30 ℃), lower temperature (17-19 ℃) could promote the sprouting of axillary buds and enhance negative gravitropism of branches, resulting in shorter rhizomes. The upward growth of branches was earlier at low temperature than that at high temperature, leading to a high frequency of shorter rhizomes and smaller branch angles. Comparative transcriptome showed that plant hormones played an essential role in the response of OL to temperature. The expressions of ARF17, ARF25 and FucT were up-regulated at low temperature, resulting in prospectively asymmetric auxin distribution, which subsequently induced asymmetric expression of IAA20 and WOX11 between the upper and lower side of the rhizome, further leading to upward growth of the rhizome. Cytokinin and auxin are phytohormones that can promote and inhibit bud outgrowth, respectively. The auxin biosynthesis gene YUCCA1 and cytokinin oxidase/dehydrogenase gene CKX4 and CKX9 were up-regulated, while cytokinin biosynthesis gene IPT4 was down-regulated at high temperature. Moreover, the D3 and D14 in strigolactones pathways, negatively regulating bud outgrowth, were up-regulated at high temperature. These results indicated that cytokinin, auxins, and strigolactones jointly control bud outgrowth at different temperatures. Our research revealed that the outgrowth of axillary bud and the upward growth of OL rhizome were earlier at lower temperature, providing clues for understanding the rhizome growth habit under different temperatures, which would be helpful for cultivating perennial rice.

Addressing future food demand in The Gambia: can increased crop productivity and climate change adaptation close the supply-demand gap?

With rising demand for food and the threats posed by climate change, The Gambia faces significant challenges in ensuring sufficient and nutritious food for its population. To address these challenges, there is a need to increase domestic food production while limiting deforestation and land degradation. In this study, we modified the FABLE Calculator, a food and land-use system model, to focus on The Gambia to simulate scenarios for future food demand and increasing domestic food production. We considered the impacts of climate change on crops, the adoption of climate change adaptation techniques, as well as the potential of enhanced fertiliser use and irrigation to boost crop productivity, and assessed whether these measures would be sufficient to meet the projected increase in food demand. Our results indicate that domestic food production on existing cropland will not be sufficient to meet national food demand by 2050, leading to a significant supply-demand gap. However, investments in fertiliser availability and the development of sustainable irrigation infrastructure, coupled with climate change adaptation strategies like the adoption of climate-resilient crop varieties and optimised planting dates, could halve this gap. Addressing the remaining gap will require additional strategies, such as increasing imports, expanding cropland, or prioritising the production of domestic food crops over export crops. Given the critical role imports play in The Gambia's food supply, it is essential to ensure a robust flow of food imports by diversifying partners and addressing regional trade barriers. Our study highlights the urgent need for sustained investment and policy support to enhance domestic food production and food imports to secure sufficient and healthy food supplies amidst growing demand and climate change challenges.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12571-024-01444-1.

Food insecurity and outcomes during COVID-19 pandemic in sub-Saharan Africa (SSA)

The outbreak of COVID-19 led to the implementation of lockdowns and social distancing regulations to curb the spread of infections. Consequently, the lockdowns impeded the movement of smallholder farmers, agricultural inputs, and food products thereby disrupting the food supply chains in SSA. Therefore, this paper examines the relationship between food security indicators (accessibility, availability, utilization, stability) and COVID-19. This study uses ordinary least square regression (OLS) models to study the relationship between the food security indicators and COVID-19. The study considers 9 out of 48 sub-Saharan African countries (Benin, Burkina Faso, Cameroon, Chad, Madagascar, Mali, Mauritania, Nigeria, Senegal) due to data availability restrictions. The result of the analysis indicated that a rise in COVID-19 levels negatively impacts all the 4 indicators of food security without exception. This paper underscores the need to consider the disruptions of food security indicators such as diet, nutritional content, access and availability, affordability, and food supply chains. Moreover, the paper discusses mitigating strategies that may alleviate SSA’s food security amidst the COVID-19 pandemic. We recommend that SSA countries invest in quality agricultural and food production infrastructure and supporting industries that contribute directly to the food supply chain, such as agro-processing, fertilizer production and transport. Another important dimension of the COVID-19 and food insecurity syndemic is the income shocks that occurred as a consequence of the COVID-19 outbreak. Like many factories, companies, and service providers closed shop (especially the informal sector), people lost their incomes as a result of loss of employment and, in many instances, no social protection. Therefore, we recommend that SSA governments develop affordable, sustainable, and targeted social protection/insurance systems that extend to the informal sector of the economy.

Spatiotemporal Heterogeneity Monitoring of Cropland Evolution and Its Impact on Grain Production Changes in the Southern Sanjiang Plain of Northeast China

High-speed cropland changes are taking place in Northeast China, bringing about the sustainable changes in ecological landscape and food production; however, the lack of continuous research limits the revelation of new findings in this region. The integrated approach of land migration tracking, ecological landscape and mathematical statistics was established to conduct a comprehensive survey of land change–landscape–food security in a typical grain-planting region of Northeast China to reveal new changes from 1990 to 2020. Results display that the cropland area continued to increase from 25,885.16 km2 in 1990 to 31,144.46 km2 in 2020, leading to the loss of forest land, grassland, water body and unused land. For cropland structure, the proportion of paddy fields in cropland increased rapidly from 7.18 to 39.53% during 1990–2020; in contrast, upland crops decreased sharply. The richness of landscape presented gradually complex characteristics with SHDI from 0.258 to 0.671 and other ecological indicators underwent similar changes with strong regularity. Total grain production displayed a continuous increase, with values from 523.79 × 104 t to 1839.12 × 104 t, increasing by 2.51 times from 1990 to 2020. We also revealed the contribution rate of unchanged upland crops to grain increments was the largest (i.e., 46.29%), and the conversion of internal cropland structure (i.e., the paddy fields converted from upland crops) contributed 12.17% from 1990 to 2020, showing a positive signal for food security. These new findings provide studies on land use change, ecological landscape and food security in China and abroad.

Efficiency Analysis of Land Use and the Degree of Coupling Link between Population Growth and Global Built-Up Area in the Subregion of West Africa

The main challenge for land use efficiency is population growth. Using a coupling coordination model and the Sustainable Development Goal 11.3.1 (Land Consumption Rate to Population Growth Rate, LCRPGR), the present study unravels the evolution of land use types and efficiency of land use in the Economic Community of West African States (ECOWAS) from 2003 to 2019. We interpreted the temporal land use types based on the long-time series Moderate Resolution Imaging Spectroradiometer (MCD12Q1-V6) land use images in 2003, 2007, 2011, 2015, and 2019. The World Bank data on population and socioeconomics were used to support the investigation on the coupled link. Our results showed that from 2003 to 2019, the total area of agricultural land decreased by −1.4%, while the built-up area expanded by 25.80%. Globally, the LCRPGR was 0.82, of which Cabo-Verdi and Niger had the highest (1.69) and lowest index (0.58), respectively. Correspondingly, the coupled coordination model indicated an overall value of 6.81, in which the highest and lowest value occurred in Liberia (29.78) and Niger (0.31), respectively. Furthermore, a rapidly growing population had become one of the most important factors causing inefficient land use in the study area. In summary, the ECOWAS was confronted with a lack of management to improve land use efficiency. Thus, future land use policies should pay more attention to balancing the coupled relationship between urban expansion and socio-economic interests.

Long-Term Dynamics and Response to Climate Change of Different Vegetation Types Using GIMMS NDVI3g Data over Amathole District in South Africa

Monitoring vegetation dynamics is essential for improving our understanding of how natural and managed agricultural landscapes respond to climate variability and change in the long term. Amathole District Municipality (ADM) in Eastern Cape Province of South Africa has been majorly threatened by climate variability and change during the last decades. This study explored long-term dynamics of vegetation and its response to climate variations using the satellite-derived normalized difference vegetation index from the third-generation Global Inventory Modeling and Mapping Studies (GIMMS NDVI3g) and the ERA5-Land global reanalysis product. A non-parametric trend and partial correlation analyses were used to evaluate the long-term vegetation changes and the role of climatic variables (temperature, precipitation, solar radiation and wind speed) during the period 1981–2015. The results of the ADM’s seasonal NDVI3g characteristics suggested that negative vegetation changes (browning trends) dominated most of the landscape from winter to summer while positive (greening) trends dominated in autumn during the study period. Much of these changes were reflected in forest landscapes with a higher coefficient of variation (CV ≈ 15) than other vegetation types (CV ≈ 10). In addition, the pixel-wise correlation analyses indicated a positive (negative) relationship between the NDVI3g and the ERA5-Land precipitation in spring–autumn (winter) seasons, while the reverse was the case with other climatic variables across vegetation types. However, the relationships between the NDVI3g and the climatic variables were relatively low (R < 0.5) across vegetation types and seasons, the results somewhat suggest the potential role of atmospheric variations in vegetation changes in ADM. The findings of this study provide invaluable insights into potential consequences of climate change and the need for well-informed decisions that underpin the evaluation and management of regional vegetation and forest resources.

Interannual variability of vegetation sensitivity to climate in China

Many studies have assessed the relative sensitivity of ecosystems to climate change, and even optimized climate states from long-term averages to infer short-term changes, but how ecosystem sensitivity and its relationships with climate variability vary over time remains elusive. By combining the vegetation sensitivity index (VSI) and a 15 year moving window, we analyzed interannual variability in spatiotemporal patterns of vegetation sensitivity to short-term climate variability and its correlations with climatic factors in China over the past three decades (1982-2015). We demonstrated that vegetation sensitivity shows high spatial heterogeneity, and varies with vegetation type and climate region. Generally, vegetation in the southwest and mountainous regions was more sensitive, especially coniferous forests and isolated shrubland patches. Comparatively, vegetation in dry regions was less sensitive to climate variability than in wetter climates. Due to frequent climate variability in the early 1990s, a large increase in the VSI was detected in 1996. Significant increases in the interannual variability of vegetation sensitivity were observed in greater than 23.7% of vegetated areas and decreases in only 4.2%. Solar radiation was the dominant climate driver of vegetation sensitivity, followed by temperature and precipitation. However, climate controls are not invariable across a range of climatic conditions, such as precipitation exerted an increasing influence on changes of vegetation sensitivity. Quantitative analyses of ecosystem sensitivity to climate variability such as ours are vital to identify which regions and vegetation are most vulnerable to future climate variability.

Agricultural Land Transition in the “Groundnut Basin” of Senegal: 2009 to 2018

The study aims to reveal the transition features of agricultural land use in the Groundnut Basin of Senegal from 2009 to 2018, especially the impact of urbanization on agricultural land and the viewpoint of farmland spatiotemporal evolution. Integrated data of time series MCD12Q1 land-use images of 2009, 2012, 2015, and 2018 were used to provide a land transition in agricultural and urban areas through the synergistic methodology. Socio-economic data was also used to serve as a basis for the argument. The results highlight that: (1) Agricultural land increased by 14.53%, with a dynamic index of 1.45 from 2009–2018. (2) Over the same period, urbanization increased by 2.80%, with a dynamic index of 0.28. (3) In different regions, the transition of agricultural land in Kaffrine is most intense (expansion rate: 22.80%). The same situation of urbanization happened in Thiès Region with a value of 7.94%. Except for Thiès, agricultural land in other regions has not yet been subject to major pressure due to urbanization. Overall, the farming system in Groundnut Basin is an extensive model, the recommendations from the point of view of land-use planning and land law are necessary to ensure efficient agricultural land management in the area.

The Role of Earth Observation in Achieving Sustainable Agricultural Production in Arid and Semi-Arid Regions of the World

Crop production is a major source of food and livelihood for many people in arid and semi-arid (ASA) regions across the world. However, due to irregular climatic events, ASA regions are affected commonly by frequent droughts that can impact food production. In addition, ASA regions in the Middle East and Africa are often characterised by political instability, which can increase population vulnerability to hunger and ill health. Remote sensing (RS) provides a platform to improve the spatial prediction of crop production and food availability, with the potential to positively impact populations. This paper, firstly, describes some of the important characteristics of agriculture in ASA regions that require monitoring to improve their management. Secondly, it demonstrates how freely available RS data can support decision-making through a cost-effective monitoring system that complements traditional approaches for collecting agricultural data. Thirdly, it illustrates the challenges of employing freely available RS data for mapping and monitoring crop area, crop status and forecasting crop yield in these regions. Finally, existing approaches used in these applications are evaluated, and the challenges associated with their use and possible future improvements are discussed. We demonstrate that agricultural activities can be monitored effectively and both crop area and crop yield can be predicted in advance using RS data. We also discuss the future challenges associated with maintaining food security in ASA regions and explore some recent advances in RS that can be used to monitor cropland and forecast crop production and yield.

Mapping Tree Height in Burkina Faso Parklands with TanDEM-X

Mapping of tree height is of great importance for management, planning, and research related to agroforestry parklands in Africa. In this paper, we investigate the potential of spotlight-mode data from the interferometric synthetic aperture radar (InSAR) satellite system TanDEM-X (TDM) for mapping of tree height in Saponé, Burkina Faso, a test site characterised by a low average canopy cover (~15%) and a mean tree height of 9.0 m. Seven TDM acquisitions from January–April 2018 are used jointly to create high-resolution (~3 m) maps of interferometric phase height and mean canopy elevation, the latter derived using a new, model-based processing approach compensating for some effects of the side-looking geometry of SAR. Compared with phase height, mean canopy elevation provides a more accurate representation of tree height variations, a better tree positioning accuracy, and better tree height estimation performance when assessed using 915 trees inventoried in situ and representing 15 different species/genera. We observe and discuss two bias effects, and we use empirical models to compensate for these effects. The best-performing model using only TDM data provides tree height estimates with a standard error (SE) of 2.8 m (31% of the average height) and a correlation coefficient of 75%. The estimation performance is further improved when TDM height data are combined with in situ measurements; this is a promising result in view of future synergies with other remote sensing techniques or ground measurement-supported monitoring of well-known trees.

Multi-Actors' Co-Implementation of Climate-Smart Village Approach in West Africa: Achievements and Lessons Learnt

Climate change and variability are significant challenges for the environment and food security worldwide. Development strategies focusing simultaneously on adaptive farming, productivity, and reducing greenhouse gas (GHG) emissions-known as climate-smart agriculture (CSA) strategies-are key to responding to these challenges. For almost a decade, within the framework of Climate Change, Agriculture and Food Security (CCAFS), World Agroforestry (ICRAF), and its partners have been using Participatory Action Research (PAR) to fully engage key stakeholders in co-creating such CSA development strategies. This includes the testing of Agricultural Research for Development (AR4D) CSA scalability options. The multidisciplinary teams include the National Research and Extension Systems (NARES), national meteorological services (NMS), non-profit organizations (NGOs), and local radio programs, among others. The CCAFS-West Africa Program, World Agroforestry-West and Central Africa (ICRAF-WCA), International Union for Conservation of Nature (IUCN), University of Reading, and Centre Régional de Formation et d'Application en Agro-météorologie et Hydrologie Opérationnelle (AGRHYMET) provide technical backstopping to the national teams. Climate information (CI) was used as an entry point to inform the development of CSA technologies and practices within Climate-Smart Villages (CSV). This groundwork has led to a greater understanding of three critical factors for successful CSV implementation: (1) Building strong partnerships to co-design and develop agricultural systems that improve ecosystem and population resilience, (2) Key stakeholders (researchers, farmers, development agents, and students) capacity strengthening through vocational and academic training, and (3) Using CI for livelihood planning at all scales. These three factors support more effective identification and testing of agricultural technologies and practices addressing climate variability and change at plot, community, and landscape levels. This paper discusses the PAR-CSA methodology and parameters for evaluation, including biophysical and social change. Keys to success, including communication, knowledge sharing tools, and scalability are also discussed. Finally, future opportunities for improvement are presented, including knowledge product development, CSA policy and investment planning, capacity building, further engagement of the private sector, and additional research on existing practices and tools.

Using Landsat satellites to assess the impact of check dams built across erosive gullies on vegetation rehabilitation

Gully erosion, a process of soil removal due to water accumulation and runoff, is a worldwide problem affecting agricultural lands. Building check dams perpendicular to the flow direction is one of the suggested control practices to stabilize this process. Though there are many studies on the effect of erosive controls on land stabilization, few examine its effect on the rehabilitation of vegetation. Here we use information from the satellites Landsat-7 (1999-2018) and Landsat-8 (2013-2018) to assess the effect of soil check dams built during 2012 across three gullies with distinct structures in a dryland area on vegetative cover and water status. We use a time series analysis technique to decompose Landsat-derived soil adjusted vegetation index (SAVI) into woody (SAVI_W) and herbaceous (iSAVI_H) contributions. The integral over the seasonal signal of the normalized difference water index (iNDWI) was used to assess changes in water status in the gully. We used herbaceous biomass collected in the field in 2014-2017 to validate iSAVI_H as a proxy of herbaceous biomass. Our results show that following the construction of the check dams, the change in woody vegetation cover is best described by a sigmoid model with an increase of ~57% (95% CI: 39%-76%; p < 0.0001), while the herbaceous vegetation increases linearly at a rate of ~71% per year (95% CI: 48%-93% y^-1; p < 0.0001). The correlation between iSAVI_H and herbaceous biomass (R² = 0.56; n = 16; p < 0.001) corroborates this increase. We found higher herbaceous productivity in the deeper gully compared to the shallower gullies but not statistically different increase rates. An increase in iNDWI of ~68% (95% CI: 43%-95%; p < 0.0001) likely implies an improved water infiltration rate that favored the vegetation expansion. Our satellite-based approach can be used to assess the impact of erosive control practices on vegetation rehabilitation in heterogeneous gullies.